Epidemiological education in The Netherlands

One of the three core policy focuses of the VvE is: fostering the quality of epidemiological education. An activity to this end is supporting and encouraging epidemiological education in the Netherlands. The VvE therefore offers the epidemiology training programs in the Netherlands space its website, to list their courses. In addition, the association wants to provide students with a clear overview of programs and courses available in The Netherlands.

The aim of this course is to learn about the principles and practice of cohort, case-control and cross-sectional studies. We will discuss design, data collection and outcome measures, as well as the major advantages and disadvantages of the different study designs.

During this course we will present and discuss the rational and use of meta-analysis. We will discuss the strengths and limitations, and provide step-by-step guidance on how to perform a meta-analysis based on examples that either has provoked discussion on their logic and methods, or that have challenged conventional beliefs in medicine and biomedical sciences.

In this course we discuss and practice the methods to assess the methodological quality of primary diagnostic test accuracy studies (QUADAS-2 instrument), the statistical models to meta-analyze the paired measures of test accuracy (bivariate meta-regression model of sensitivity and specificity), and how to critically read and interpret the findings of systematic review of diagnostic studies.

In this course we discuss and practice how to define your review questions, how to critically assess the methodological quality of primary prognostic studies, and which statistical methods to use for meta-analyses of the results of primary prognostic studies.

The aim of this course is to provide you with the knowledge to evaluate and assess applied clinical research and data analyses, and give you sufficient scientific and methodological background information to actively participate in clinical studies.

Diagnostic research in the past focused particularly on estimating the sensitivity and specificity of individual diagnostic tests. This course will demonstrate that this so called ‘test research’ is not necessarily the same as diagnostic research.

This course provides a thorough medical education of clinical trials, covering the principles of therapeutic research design, including design of study, design of data collection, design of data analysis, including some modelling techniques in the analysis to clinical trials, and the interpretation of its results.

The aim of this course is to learn about the principles and practice of cohort, case-control and cross-sectional studies. We will discuss design, data collection and outcome measures, as well as the major advantages and disadvantages of the different study designs.

This course provides you with this indispensable knowledge, and ensures you are confident in analyzing medical research data and understanding the basic biostatistical applications upon which it is based.

During this course we will present and discuss the rational and use of meta-analysis. We will discuss the strengths and limitations, and provide step-by-step guidance on how to perform a meta-analysis based on examples that either has provoked discussion on their logic and methods, or that have challenged conventional beliefs in medicine and biomedical sciences.

In this course we discuss and practice the methods to assess the methodological quality of primary diagnostic test accuracy studies (QUADAS-2 instrument), the statistical models to meta-analyze the paired measures of test accuracy (bivariate meta-regression model of sensitivity and specificity), and how to critically read and interpret the findings of systematic review of diagnostic studies.

In this course we discuss and practice how to define your review questions, how to critically assess the methodological quality of primary prognostic studies, and which statistical methods to use for meta-analyses of the results of primary prognostic studies.

The aim of this course is to provide you with the knowledge to evaluate and assess applied clinical research and data analyses, and give you sufficient scientific and methodological background information to actively participate in clinical studies.

Diagnostic research in the past focused particularly on estimating the sensitivity and specificity of individual diagnostic tests. This course will demonstrate that this so called ‘test research’ is not necessarily the same as diagnostic research.

This course provides a thorough medical education of clinical trials, covering the principles of therapeutic research design, including design of study, design of data collection, design of data analysis, including some modelling techniques in the analysis to clinical trials, and the interpretation of its results.

This module is intended for health care researchers and professionals who work in academia, health care, government, consultancy or the pharmaceutical and medical device industry who wish to learn about modeling for health economic evaluation

All lectures, tutorials and practicals are planned on the Tuesdays and the Fridays

Maastricht

This module is the first module on HTA. It provides an in-depth explanation of full economic evaluations in all its steps based on effectiveness studies (cohort studies, case-control studies, randomised controlled trials)

In this module, students will be familarized with different types of biomarkers that can be used in epidemiological studies, including those measured with novel high-troughput -omics technologies, and the study designs used in molecular and genetic epidemiology.

The main aim of this four week course is to familiarize the students with the results of epidemiological research into the occurrence and the determinants of some common diseases and disease processes.

The first day of the course starts with an overview of the different types of "what if" questions raised in public health, and an overview of the types of models that could be used to address such questions. Next we will briefly discuss population projection techniques.

This course focuses on the design and the evaluation of health care programmes for the early detection of disease or screening. Screening takes place in a population without symptoms of the disease. The screening test characteristics have consequences for the favourable (improvement of prognosis by early detection, life years saved and deaths prevented) and unfavourable (overdiagnosis, unnecessary treatments) effects of screening.

The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers.

Those of us who work in health care know that promising research results or evidence-based guidelines do not easily become standard of clinical care.
Therefore, a next step, also known as implementation and dissemination, is needed after the results of a RCT or guidelines are published.
The field of implementation science has emerged, and this multidisciplinary field with professionals from medicine, nursing, psychology, pharmacy, engineering, aims to enhance the uptake of research-based knowledge in real-world settings.

4 days Wednesday to Friday, exam is Friday (17-03-2020) after class week.

Prognostic models are increasingly published in the medical literature each year. But are the results relevant for clinical practice? What are the critical elements of a well developed prognostic model? How can we assume that the model makes accurate predictions for our patients, and not only for the sample that was used to develop the model (generalizability, or external validity)?

Survival analysis is the study of the distribution of life times, i.e. the times from an initiating event (birth, diagnosis, start of treatment) to some terminal event (relapse, death). Survival analysis is most prominently (but not only) used in the biomedical sciences. A special feature of survival data is that it takes time to observe the event of interest.

This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.

R has recently become one of the most popular languages for data analysis and statistics. This course teaches students the basics syntax and data types of this statistical programming language. The aim of this course is to equip students with the R knowledge needed to explore their own data, make data visualizations and perform basic statistical analysis.

Cancer is a major cause of morbidity and mortality in the developed world. The aim of this 5-day course is to provide an overview of the contributions of exogenous and endogenous factors to the risk of various cancers

Psychiatric problems frequently occur in children and adolescents. Epidemiological methods are used in child psychiatric research to study the occurrence of psychiatric disorders, test causal hypotheses and investigate the developmental trajectories.

There is growing acknowledgement of the value of Bayesian methods for complex models in biostatistics and epidemiology, in dealing with issues such as multiplicity, measurement error, spatial associations and hierarchical structure. This course will introduce the essentials of Bayesian ideas, emphasizing practical application using exact and simulation-based software.

This module aims to teach methods to assess the health of populations in low and middel income countries and to quantitatively evaluate the effects of interventions on population health. Students are taught use modern techniques as health impact assessment to predict changes in population health due to particular programmes, for example control programmes for infectious diseases.

Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. The overall objective of the cardiovascular epidemiology course is to produce epidemiologists and other health scientists with the essential knowledge to carry out high quality research in cardiovascular disease.

This course elaborates on successful ingredients for different phases of an intervention study: design, data collection and implementation. The focus is on learning from encountered difficulties, mistakes and failures from previous research and researchers.

This 3-day course aims to give an overview of recent developments in drawing causal inferences from epidemiological data using Mendelian randomization and is aimed at individuals with a background in statistics or epidemiology with a strong statistics component. Theoretical discussion will be accompanied by introduction to available software and lab practicals.

This week-long, project-based course aims to provide students with an understanding of advanced methods used in decision-analytic modeling and cost-effectiveness analyses. These include topics like the latest methods for calibration and validation, quantifying uncertainty, and consideration of heterogeneity of patient benefits and equity issues.

The aim of the course is to provide the participants first, with a review of the instruments currently available; Second, participants are provided with the knowledge required to select measures of quality of life that are both valid and sensitive for the research objectives of the participants;